Download Advances in Intelligence and Security Informatics by Wenji Mao PDF

By Wenji Mao

The clever platforms sequence contains titles that current cutting-edge wisdom and the newest advances in clever platforms. Its scope contains theoretical reviews, layout equipment, and real-world implementations and applications.

Traditionally, Intelligence and protection Informatics (ISI) learn and purposes have all for details sharing and information mining, social community research, infrastructure safeguard and emergency responses for safeguard informatics. With the continual increase of IT applied sciences and the expanding sophistication of nationwide and overseas safety, in recent times, new instructions in ISI examine and functions have emerged to handle complex issues of complex applied sciences. This ebook offers a accomplished and interdisciplinary account of the hot advances in ISI region alongside 3 primary dimensions: methodological concerns in protection informatics; new technological advancements to help security-related modeling, detection, research and prediction; and functions and integration in interdisciplinary socio-cultural fields.

      • Identifies rising instructions in ISI study and functions that handle the learn demanding situations with complicated applied sciences
      • Provides an built-in account of the recent advances in ISI box in 3 center features: technique, technological advancements and functions
      • Benefits researchers in addition to defense pros who're interested in state-of-the-art learn and functions in safety informatics and similar fields

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      Find_house). Suppose now we observe two actions that have been executed, raise_fund and buy_house. We may find several explanations for raise_fund: SE11 = {launch_attack, bomb_attack, raise_fund}, SE12 = {launch_attack, arm_attack, raise_fund}, and SE13 = {setup_base, raise_fund}; and an explanation for buy_house: SE2 = {setup_base, find_house, buy_house}. Possible explanations for raise_fund and buy_house include E1 = SE11 ∪ SE2, E2 = SE12 ∪ SE2, and E3 = SE13 ∪ SE2. 3 The Proposed MPR Approach In this section, we propose a probabilistic approach for recognizing multiple plans.

      00004-X Copyright © 2012 Elsevier Inc. All rights reserved. 33 34 Chapter 4 key for intention recognition; assessing agents’ freedom and choice in acting—key for the assessment of power and control; and detecting how an agent’s plan facilitates or prevents the plan execution of other agents—key for the detection of intervention. In addition to proposing this computational approach, we conduct an experiment to evaluate the proposed approach in group behavior prediction. 1 Review of Plan-Based Inference Plan inference (or plan recognition) is the process of inferring the plans and goals of the observed agent based on a sequence of observations, usually with the help of a set of predefined recipes (called a plan library), which comprises the knowledge and action steps that can be performed by the agent.

      Convergence point). e. 1). In addition, we compared the answers of human raters with the 1-best and 2-best results of the algorithms. 2). Bayesian reasoning also improves considerably in the 2-best case. 26% (for 2-best). 326 Ave. 5 Conclusion Group behavior prediction is an emerging research and application field that has attracted increasing attention in recent years. It provides an ideal testbed for practicing and evaluating plan inference approaches. In this chapter, we present a plan-based approach to group behavior forecasting based on the principle of maximizing expected plan utility.

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